Performability relates the performance (throughput) and reliability of software systems whose normal behaviour may degrade owing to the existence of faults. These systems, naturally modelled as discrete event systems ...
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Performability relates the performance (throughput) and reliability of software systems whose normal behaviour may degrade owing to the existence of faults. These systems, naturally modelled as discrete event systems using shared resources, can incorporate fault-tolerant techniques to mitigate such a degradation. In this article, compositional fault-tolerant models based on Petri nets, which make its sensitive performability analysis easier, are proposed. Besides, two methods to compensate existence of faults are provided: an iterative algorithm to compute the number of extra resources needed, and an integer-linear programming problem that minimises the cost of incrementing resources and/or decrementing fault-tolerant activities. The applicability of the developed methods is shown on a Petri net that models a secure database system.
The increasing size and complexity of communication satellites has made the manual management of their payloads by engineers through computerised schematics difficult and error prone. This article proposes to optimise...
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ISBN:
(纸本)9783642284908
The increasing size and complexity of communication satellites has made the manual management of their payloads by engineers through computerised schematics difficult and error prone. This article proposes to optimise payload reconfigurations for current and next generation satellites using a novel integerlinearprogramming model (ILP), which is a variant of network flow models. Experimental results using CPLEX demonstrate the efficiency and scalability of the approach up to realistic satellite payloads sizes and configurations.
Sudden service disruption due to natural or man-made disaster is one of the major threats to commercial supply chains and military logistics at present. In this paper, we present an integer-linear programming model fo...
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ISBN:
(纸本)9780769538044
Sudden service disruption due to natural or man-made disaster is one of the major threats to commercial supply chains and military logistics at present. In this paper, we present an integer-linear programming model for critical facilities protection based on time satisfaction, which could overcome the weakness of simply using time and distance in previous researches. The objective function is maximizing time satisfaction of the system in every elimination pattern. Then we combine genetic algorithms (GAs) with simulated annealing to solve this model. At the end, a numerical example is used to illustrate the application of the model, which shows the method is feasible and efficient.
We introduce new penalties, called valid integer polytope (VIP) penalties, that tighten the bound of an integer-linear program during branch-acid-bound enumeration. Early commercial codes for branch and bound commonly...
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We introduce new penalties, called valid integer polytope (VIP) penalties, that tighten the bound of an integer-linear program during branch-acid-bound enumeration. Early commercial codes for branch and bound commonly employed penalties developed from the dual simplicial lower bound on the cost of restricting fractional integer variables to proximate integral values. VIP penalties extend and tighten these for ubiquitous k-pack, k-partition, and K-cover constraints. In real-world problems, VIP penalties occasionally tighten the bound by more than an order of magnitude, but they usually offer small bound improvement. Their ease of implementation, speed of execution, and occasional, overwhelming success make them an attractive addition during branch-and-bound enumeration. (C) 2000 Elsevier Science B.V. All rights reserved.
The economic scheduling of power generation is considered, and an improved algorithm based on a combination of mixed integer-linear and dynamic programming presented. Mixed integer-linear programming is used to determ...
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The economic scheduling of power generation is considered, and an improved algorithm based on a combination of mixed integer-linear and dynamic programming presented. Mixed integer-linear programming is used to determine feasible combinations of units at each scheduling point, while a novel dynamic programming approach identifies promising scheduling routes in the time domain. The algorithm obtains the same solutions as mixed integer-linear programming, but with significant savings in the solution times required and the amount of computer memory used.
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